Reduction started at: 20041115-150848 Reading data from /net/moana/export/data/janw/rxh3/rxh3-20041111-190003.fits Reduction ID: default Read keywords into global array holo_keys Read binary table data into global array holo_data Finished reading data Converted positions to arcsec, times to elapsed seconds, and reversed x-axis Pattern extent: min = 2402.8 max = 2431.5 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.880 mm ----------------- Data Summary --------------------- Number of samples: 370025 This is a 80 GHz map Number of frequencies: 16 Frequencies (GHz): 80.338000 80.340000 80.342000 80.344000 80.346000 80.348000 80.350000 80.352000 80.354000 80.356000 80.358000 80.360000 80.362000 80.364000 80.366000 80.368000 item min max mean loreal -3.11035 3.12500 -0.02756 loimag -3.23242 3.15674 0.01161 hireal -5.00000 4.99756 -0.48909 hiimag -5.00000 4.99756 -0.14044 xpos -2431.54725 2418.67417 -7.90576 ypos -2402.97594 2402.75816 -0.00601 plock160 0.39307 1.86279 1.18685 lorefpwr 0.26123 1.65283 1.21029 losigpwr -4.53125 -0.22217 -4.35098 hirefpwr 0.32471 1.68457 1.25492 hisigpwr -4.43848 4.99756 -0.69189 encltemp 31.59180 32.78809 32.10469 flags 0.00000 256.00000 2.76738 phi-lock -1.63818 -0.25391 -0.96537 sindex 0.00000 128.00000 63.61104 time 0.00000 2947.98190 1473.09002 zeropt -0.00732 -0.00244 -0.00489 !!!Warning!!! philock max less than 0.2 !!!Warning!!! philock min less than -1.5 ---------------------------------------------------- Subtracting zeropt channel Data contains a total of 129 rows There are 121 data rows and 8 calibrator rows Calibrator rows: 0 21 42 63 84 105 126 128 Checking pointing along rasters... This map is more horizontally scanned than vertically Mean row spacing = 40.00633 arcsec Mean row spacing = 40.00635 arcsec (alternate estimator) Mean tracking incline = -0.25523 arcsec Mean pointing range = 0.75405 arcsec Mean pointing rms = 0.15296 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (-1.50, 15.80 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 Doing geometric phase correction Status bits counts: bit: 0 1 2 3 4 5 6 7 8 set: 0 0 0 0 0 0 0 0 4000 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22683 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22683 data points No calibration requested... Creating template maps for gridding Using a grid cellsize of 40.0 arcseconds Using a grid of 128 points Grid has even number of points Maximum data offset = 2431.55 arcsec Grid extent = 2540 arcsec lambda_min = 0.00373025 scale = 0.00129968 Diffraction scale lambda/D = 51.3137 arcsec Gridding function extent = 307.882 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 153.941 arcsec Airy first null at 62.5858 arcsec Gridding frequency index 0 lambda = 0.00373164 metres, scale = 0.0012992 radians per metre Gridding real part of frequency 0... Gridding imag part of frequency 0... Pattern is holo(res.pattern0) Weights in holo(obs.real,wt0) and holo(obs.imag,wt0) Maximum amplitude = 2.96517 at (0.0, 0.0) arcsec Real: mean = 0.00127808 sum of squares = 957.603 Imag: mean = -0.0024052 sum of squares = 992.726 Gridding frequency index 1 lambda = 0.00373155 metres, scale = 0.00129923 radians per metre Gridding real part of frequency 1... Gridding imag part of frequency 1... Pattern is holo(res.pattern1) Weights in holo(obs.real,wt1) and holo(obs.imag,wt1) Maximum amplitude = 2.97714 at (0.0, 0.0) arcsec Real: mean = 0.00159779 sum of squares = 889.101 Imag: mean = -0.00283765 sum of squares = 1061.6 Gridding frequency index 2 lambda = 0.00373145 metres, scale = 0.00129926 radians per metre Gridding real part of frequency 2... Gridding imag part of frequency 2... Pattern is holo(res.pattern2) Weights in holo(obs.real,wt2) and holo(obs.imag,wt2) Maximum amplitude = 3.00988 at (0.0, 0.0) arcsec Real: mean = 0.0021595 sum of squares = 878.174 Imag: mean = -0.00312373 sum of squares = 1074.12 Gridding frequency index 3 lambda = 0.00373136 metres, scale = 0.00129929 radians per metre Gridding real part of frequency 3... Gridding imag part of frequency 3... Pattern is holo(res.pattern3) Weights in holo(obs.real,wt3) and holo(obs.imag,wt3) Maximum amplitude = 3.04645 at (0.0, 0.0) arcsec Real: mean = 0.00278073 sum of squares = 939.496 Imag: mean = -0.00301776 sum of squares = 1016.45 Gridding frequency index 4 lambda = 0.00373127 metres, scale = 0.00129933 radians per metre Gridding real part of frequency 4... Gridding imag part of frequency 4... Pattern is holo(res.pattern4) Weights in holo(obs.real,wt4) and holo(obs.imag,wt4) Maximum amplitude = 3.09835 at (0.0, 0.0) arcsec Real: mean = 0.0031596 sum of squares = 1033.99 Imag: mean = -0.00271955 sum of squares = 927.392 Gridding frequency index 5 lambda = 0.00373118 metres, scale = 0.00129936 radians per metre Gridding real part of frequency 5... Gridding imag part of frequency 5... Pattern is holo(res.pattern5) Weights in holo(obs.real,wt5) and holo(obs.imag,wt5) Maximum amplitude = 3.1448 at (0.0, 0.0) arcsec Real: mean = 0.00340801 sum of squares = 1091.13 Imag: mean = -0.00235973 sum of squares = 877.846 Gridding frequency index 6 lambda = 0.00373108 metres, scale = 0.00129939 radians per metre Gridding real part of frequency 6... Gridding imag part of frequency 6... Pattern is holo(res.pattern6) Weights in holo(obs.real,wt6) and holo(obs.imag,wt6) Maximum amplitude = 3.17269 at (0.0, 0.0) arcsec Real: mean = 0.00353845 sum of squares = 1068.16 Imag: mean = -0.00188953 sum of squares = 906.083 Gridding frequency index 7 lambda = 0.00373099 metres, scale = 0.00129942 radians per metre Gridding real part of frequency 7... Gridding imag part of frequency 7... Pattern is holo(res.pattern7) Weights in holo(obs.real,wt7) and holo(obs.imag,wt7) Maximum amplitude = 3.16869 at (0.0, 0.0) arcsec Real: mean = 0.00351524 sum of squares = 984.816 Imag: mean = -0.00145187 sum of squares = 994.396 Gridding frequency index 8 lambda = 0.0037309 metres, scale = 0.00129946 radians per metre Gridding real part of frequency 8... Gridding imag part of frequency 8... Pattern is holo(res.pattern8) Weights in holo(obs.real,wt8) and holo(obs.imag,wt8) Maximum amplitude = 3.14493 at (0.0, 0.0) arcsec Real: mean = 0.00325039 sum of squares = 905.673 Imag: mean = -0.000924692 sum of squares = 1076.48 Gridding frequency index 9 lambda = 0.0037308 metres, scale = 0.00129949 radians per metre Gridding real part of frequency 9... Gridding imag part of frequency 9... Pattern is holo(res.pattern9) Weights in holo(obs.real,wt9) and holo(obs.imag,wt9) Maximum amplitude = 3.10396 at (0.0, 0.0) arcsec Real: mean = 0.00269745 sum of squares = 891.435 Imag: mean = -0.000605341 sum of squares = 1093.55 Gridding frequency index 10 lambda = 0.00373071 metres, scale = 0.00129952 radians per metre Gridding real part of frequency 10... Gridding imag part of frequency 10... Pattern is holo(res.pattern10) Weights in holo(obs.real,wt10) and holo(obs.imag,wt10) Maximum amplitude = 3.07054 at (0.0, 0.0) arcsec Real: mean = 0.00206665 sum of squares = 951.043 Imag: mean = -0.000723061 sum of squares = 1036.54 Gridding frequency index 11 lambda = 0.00373062 metres, scale = 0.00129955 radians per metre Gridding real part of frequency 11... Gridding imag part of frequency 11... Pattern is holo(res.pattern11) Weights in holo(obs.real,wt11) and holo(obs.imag,wt11) Maximum amplitude = 3.03575 at (0.0, 0.0) arcsec Real: mean = 0.00169687 sum of squares = 1042.1 Imag: mean = -0.00114385 sum of squares = 949.749 Gridding frequency index 12 lambda = 0.00373053 metres, scale = 0.00129959 radians per metre Gridding real part of frequency 12... Gridding imag part of frequency 12... Pattern is holo(res.pattern12) Weights in holo(obs.real,wt12) and holo(obs.imag,wt12) Maximum amplitude = 3.02271 at (0.0, 0.0) arcsec Real: mean = 0.00161619 sum of squares = 1099.75 Imag: mean = -0.00150074 sum of squares = 896.158 Gridding frequency index 13 lambda = 0.00373043 metres, scale = 0.00129962 radians per metre Gridding real part of frequency 13... Gridding imag part of frequency 13... Pattern is holo(res.pattern13) Weights in holo(obs.real,wt13) and holo(obs.imag,wt13) Maximum amplitude = 3.01043 at (0.0, 0.0) arcsec Real: mean = 0.00160499 sum of squares = 1085.46 Imag: mean = -0.00178223 sum of squares = 912.613 Gridding frequency index 14 lambda = 0.00373034 metres, scale = 0.00129965 radians per metre Gridding real part of frequency 14... Gridding imag part of frequency 14... Pattern is holo(res.pattern14) Weights in holo(obs.real,wt14) and holo(obs.imag,wt14) Maximum amplitude = 3.0252 at (0.0, 0.0) arcsec Real: mean = 0.00153963 sum of squares = 1011.73 Imag: mean = -0.00213805 sum of squares = 988.056 Gridding frequency index 15 lambda = 0.00373025 metres, scale = 0.00129968 radians per metre Gridding real part of frequency 15... Gridding imag part of frequency 15... Pattern is holo(res.pattern15) Weights in holo(obs.real,wt15) and holo(obs.imag,wt15) Maximum amplitude = 3.04273 at (0.0, 0.0) arcsec Real: mean = 0.0017584 sum of squares = 929.288 Imag: mean = -0.00275777 sum of squares = 1072.87 Masking frequency index 0 Mask scale size = 3.05922 Masking frequency index 1 Mask scale size = 3.0593 Masking frequency index 2 Mask scale size = 3.05938 Masking frequency index 3 Mask scale size = 3.05945 Masking frequency index 4 Mask scale size = 3.05953 Masking frequency index 5 Mask scale size = 3.05961 Masking frequency index 6 Mask scale size = 3.05968 Masking frequency index 7 Mask scale size = 3.05976 Masking frequency index 8 Mask scale size = 3.05983 Masking frequency index 9 Mask scale size = 3.05991 Masking frequency index 10 Mask scale size = 3.05999 Masking frequency index 11 Mask scale size = 3.06006 Masking frequency index 12 Mask scale size = 3.06014 Masking frequency index 13 Mask scale size = 3.06021 Masking frequency index 14 Mask scale size = 3.06029 Masking frequency index 15 Mask scale size = 3.06037 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.183105 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.197754 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.180664 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.178223 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.180664 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.183105 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.180664 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.0170898 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -0.26854 107.88 Freq 1: Shift, scale = -0.70864 106.58 Freq 2: Shift, scale = -1.1471 104.86 Freq 3: Shift, scale = -1.5855 103.31 Freq 4: Shift, scale = -2.0242 102.01 Freq 5: Shift, scale = -2.4683 101.91 Freq 6: Shift, scale = -2.9158 102.65 Freq 7: Shift, scale = 2.9207 104.12 Freq 8: Shift, scale = 2.4773 105.82 Freq 9: Shift, scale = 2.0365 107.39 Freq 10: Shift, scale = 1.5996 108.83 Freq 11: Shift, scale = 1.1649 109.92 Freq 12: Shift, scale = 0.73447 110.34 Freq 13: Shift, scale = 0.30226 110.03 Freq 14: Shift, scale = -0.12802 109.18 Freq 15: Shift, scale = -0.55903 107.49 Calculating phase corrections for index 0 Calculating phase corrections for index 1 Calculating phase corrections for index 2 Calculating phase corrections for index 3 Calculating phase corrections for index 4 Calculating phase corrections for index 5 Calculating phase corrections for index 6 Calculating phase corrections for index 7 Calculating phase corrections for index 8 Calculating phase corrections for index 9 Calculating phase corrections for index 10 Calculating phase corrections for index 11 Calculating phase corrections for index 12 Calculating phase corrections for index 13 Calculating phase corrections for index 14 Calculating phase corrections for index 15 Apply near field corrections for frequency 0 Apply secondary diffraction correction for frequency 0 Apply near field corrections for frequency 1 Apply secondary diffraction correction for frequency 1 Apply near field corrections for frequency 2 Apply secondary diffraction correction for frequency 2 Apply near field corrections for frequency 3 Apply secondary diffraction correction for frequency 3 Apply near field corrections for frequency 4 Apply secondary diffraction correction for frequency 4 Apply near field corrections for frequency 5 Apply secondary diffraction correction for frequency 5 Apply near field corrections for frequency 6 Apply secondary diffraction correction for frequency 6 Apply near field corrections for frequency 7 Apply secondary diffraction correction for frequency 7 Apply near field corrections for frequency 8 Apply secondary diffraction correction for frequency 8 Apply near field corrections for frequency 9 Apply secondary diffraction correction for frequency 9 Apply near field corrections for frequency 10 Apply secondary diffraction correction for frequency 10 Apply near field corrections for frequency 11 Apply secondary diffraction correction for frequency 11 Apply near field corrections for frequency 12 Apply secondary diffraction correction for frequency 12 Apply near field corrections for frequency 13 Apply secondary diffraction correction for frequency 13 Apply near field corrections for frequency 14 Apply secondary diffraction correction for frequency 14 Apply near field corrections for frequency 15 Apply secondary diffraction correction for frequency 15 Fitting piston, pointing and defocus terms Fitting frequency 0 Minimiser fit code = 3 piston: -0.223 radians x offset: -0.0368 arcsec y offset: 0.0903 arcsec defocus: -0.0112 mm Estimated x pointing error is -1.537 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.89 arcsec (used 15.8 arcsec) Estimated defocus error is 2.869 mm (used 2.88 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.225 radians x offset: -0.0372 arcsec y offset: 0.0954 arcsec defocus: -0.013 mm Estimated x pointing error is -1.537 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.9 arcsec (used 15.8 arcsec) Estimated defocus error is 2.867 mm (used 2.88 mm) Fitting frequency 2 Minimiser fit code = 3 piston: -0.227 radians x offset: -0.0447 arcsec y offset: 0.102 arcsec defocus: -0.0148 mm Estimated x pointing error is -1.545 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.9 arcsec (used 15.8 arcsec) Estimated defocus error is 2.865 mm (used 2.88 mm) Fitting frequency 3 Minimiser fit code = 3 piston: -0.229 radians x offset: -0.0613 arcsec y offset: 0.122 arcsec defocus: -0.0158 mm Estimated x pointing error is -1.561 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.92 arcsec (used 15.8 arcsec) Estimated defocus error is 2.864 mm (used 2.88 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.23 radians x offset: -0.0751 arcsec y offset: 0.128 arcsec defocus: -0.0151 mm Estimated x pointing error is -1.575 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.93 arcsec (used 15.8 arcsec) Estimated defocus error is 2.865 mm (used 2.88 mm) Fitting frequency 5 Minimiser fit code = 3 piston: -0.235 radians x offset: -0.0873 arcsec y offset: 0.142 arcsec defocus: -0.012 mm Estimated x pointing error is -1.587 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.94 arcsec (used 15.8 arcsec) Estimated defocus error is 2.868 mm (used 2.88 mm) Fitting frequency 6 Minimiser fit code = 3 piston: -0.243 radians x offset: -0.0851 arcsec y offset: 0.124 arcsec defocus: -0.00947 mm Estimated x pointing error is -1.585 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.92 arcsec (used 15.8 arcsec) Estimated defocus error is 2.871 mm (used 2.88 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.251 radians x offset: -0.0693 arcsec y offset: 0.0987 arcsec defocus: -0.00918 mm Estimated x pointing error is -1.569 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.9 arcsec (used 15.8 arcsec) Estimated defocus error is 2.871 mm (used 2.88 mm) Fitting frequency 8 Minimiser fit code = 3 piston: -0.257 radians x offset: -0.0287 arcsec y offset: 0.0662 arcsec defocus: -0.0108 mm Estimated x pointing error is -1.529 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.87 arcsec (used 15.8 arcsec) Estimated defocus error is 2.869 mm (used 2.88 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.259 radians x offset: 5.48e-05 arcsec y offset: 0.0378 arcsec defocus: -0.0103 mm Estimated x pointing error is -1.5 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.84 arcsec (used 15.8 arcsec) Estimated defocus error is 2.87 mm (used 2.88 mm) Fitting frequency 10 Minimiser fit code = 3 piston: -0.259 radians x offset: 0.0268 arcsec y offset: 0.0126 arcsec defocus: -0.0132 mm Estimated x pointing error is -1.473 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.81 arcsec (used 15.8 arcsec) Estimated defocus error is 2.867 mm (used 2.88 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.256 radians x offset: 0.0373 arcsec y offset: -0.000611 arcsec defocus: -0.015 mm Estimated x pointing error is -1.463 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.8 arcsec (used 15.8 arcsec) Estimated defocus error is 2.865 mm (used 2.88 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.25 radians x offset: 0.0615 arcsec y offset: -0.00181 arcsec defocus: -0.0195 mm Estimated x pointing error is -1.439 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.8 arcsec (used 15.8 arcsec) Estimated defocus error is 2.86 mm (used 2.88 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.242 radians x offset: 0.0663 arcsec y offset: 0.016 arcsec defocus: -0.0199 mm Estimated x pointing error is -1.434 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.82 arcsec (used 15.8 arcsec) Estimated defocus error is 2.86 mm (used 2.88 mm) Fitting frequency 14 Minimiser fit code = 3 piston: -0.233 radians x offset: 0.054 arcsec y offset: 0.0468 arcsec defocus: -0.0196 mm Estimated x pointing error is -1.446 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.85 arcsec (used 15.8 arcsec) Estimated defocus error is 2.86 mm (used 2.88 mm) Fitting frequency 15 Minimiser fit code = 3 piston: -0.225 radians x offset: 0.0416 arcsec y offset: 0.0504 arcsec defocus: -0.0181 mm Estimated x pointing error is -1.458 arcsec (used -1.5 arcsec) Estimated y pointing error is 15.85 arcsec (used 15.8 arcsec) Estimated defocus error is 2.862 mm (used 2.88 mm) Making masked surfaces in microns, and cubes Fitting Zernikes Fitting many Zernikes for frequency 0 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00069 piston 1 1 -0.01223 tilt_x 1 -1 0.00922 tilt_y 2 2 0.02515 astigmatism_0 2 0 0.00305 curvature 2 -2 -0.01172 astigmatism45 3 3 0.01958 trefoil_0 3 1 -0.04096 coma_x 3 -1 0.02957 coma_y 3 -3 0.01866 trefoil_30 Fitting many Zernikes for frequency 1 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00074 piston 1 1 -0.01203 tilt_x 1 -1 0.00953 tilt_y 2 2 0.02378 astigmatism_0 2 0 0.00331 curvature 2 -2 -0.01091 astigmatism45 3 3 0.01982 trefoil_0 3 1 -0.03988 coma_x 3 -1 0.03014 coma_y 3 -3 0.01985 trefoil_30 Fitting many Zernikes for frequency 2 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00080 piston 1 1 -0.01104 tilt_x 1 -1 0.01032 tilt_y 2 2 0.02324 astigmatism_0 2 0 0.00367 curvature 2 -2 -0.01105 astigmatism45 3 3 0.01908 trefoil_0 3 1 -0.03669 coma_x 3 -1 0.03227 coma_y 3 -3 0.01866 trefoil_30 Fitting many Zernikes for frequency 3 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00081 piston 1 1 -0.01062 tilt_x 1 -1 0.01160 tilt_y 2 2 0.02307 astigmatism_0 2 0 0.00378 curvature 2 -2 -0.01122 astigmatism45 3 3 0.01864 trefoil_0 3 1 -0.03514 coma_x 3 -1 0.03586 coma_y 3 -3 0.01886 trefoil_30 Fitting many Zernikes for frequency 4 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00079 piston 1 1 -0.00982 tilt_x 1 -1 0.01228 tilt_y 2 2 0.02425 astigmatism_0 2 0 0.00379 curvature 2 -2 -0.01121 astigmatism45 3 3 0.01745 trefoil_0 3 1 -0.03303 coma_x 3 -1 0.03762 coma_y 3 -3 0.01798 trefoil_30 Fitting many Zernikes for frequency 5 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00074 piston 1 1 -0.00952 tilt_x 1 -1 0.01268 tilt_y 2 2 0.02658 astigmatism_0 2 0 0.00353 curvature 2 -2 -0.01207 astigmatism45 3 3 0.01661 trefoil_0 3 1 -0.03263 coma_x 3 -1 0.03898 coma_y 3 -3 0.01772 trefoil_30 Fitting many Zernikes for frequency 6 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00066 piston 1 1 -0.00957 tilt_x 1 -1 0.01219 tilt_y 2 2 0.02852 astigmatism_0 2 0 0.00309 curvature 2 -2 -0.01215 astigmatism45 3 3 0.01685 trefoil_0 3 1 -0.03339 coma_x 3 -1 0.03777 coma_y 3 -3 0.01805 trefoil_30 Fitting many Zernikes for frequency 7 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00059 piston 1 1 -0.00962 tilt_x 1 -1 0.01164 tilt_y 2 2 0.03031 astigmatism_0 2 0 0.00269 curvature 2 -2 -0.01200 astigmatism45 3 3 0.01619 trefoil_0 3 1 -0.03427 coma_x 3 -1 0.03647 coma_y 3 -3 0.01796 trefoil_30 Fitting many Zernikes for frequency 8 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00057 piston 1 1 -0.00981 tilt_x 1 -1 0.01068 tilt_y 2 2 0.03057 astigmatism_0 2 0 0.00253 curvature 2 -2 -0.01268 astigmatism45 3 3 0.01754 trefoil_0 3 1 -0.03497 coma_x 3 -1 0.03423 coma_y 3 -3 0.01978 trefoil_30 Fitting many Zernikes for frequency 9 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00058 piston 1 1 -0.01049 tilt_x 1 -1 0.01025 tilt_y 2 2 0.02934 astigmatism_0 2 0 0.00244 curvature 2 -2 -0.01307 astigmatism45 3 3 0.01746 trefoil_0 3 1 -0.03677 coma_x 3 -1 0.03329 coma_y 3 -3 0.02160 trefoil_30 Fitting many Zernikes for frequency 10 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00061 piston 1 1 -0.01080 tilt_x 1 -1 0.01008 tilt_y 2 2 0.02902 astigmatism_0 2 0 0.00250 curvature 2 -2 -0.01386 astigmatism45 3 3 0.01790 trefoil_0 3 1 -0.03781 coma_x 3 -1 0.03307 coma_y 3 -3 0.02162 trefoil_30 Fitting many Zernikes for frequency 11 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00066 piston 1 1 -0.01138 tilt_x 1 -1 0.00996 tilt_y 2 2 0.02773 astigmatism_0 2 0 0.00259 curvature 2 -2 -0.01409 astigmatism45 3 3 0.01673 trefoil_0 3 1 -0.03926 coma_x 3 -1 0.03279 coma_y 3 -3 0.02192 trefoil_30 Fitting many Zernikes for frequency 12 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00071 piston 1 1 -0.01138 tilt_x 1 -1 0.01006 tilt_y 2 2 0.02764 astigmatism_0 2 0 0.00282 curvature 2 -2 -0.01421 astigmatism45 3 3 0.01580 trefoil_0 3 1 -0.03930 coma_x 3 -1 0.03303 coma_y 3 -3 0.02082 trefoil_30 Fitting many Zernikes for frequency 13 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00078 piston 1 1 -0.01134 tilt_x 1 -1 0.01038 tilt_y 2 2 0.02742 astigmatism_0 2 0 0.00312 curvature 2 -2 -0.01457 astigmatism45 3 3 0.01501 trefoil_0 3 1 -0.03909 coma_x 3 -1 0.03389 coma_y 3 -3 0.01878 trefoil_30 Fitting many Zernikes for frequency 14 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00084 piston 1 1 -0.01151 tilt_x 1 -1 0.01104 tilt_y 2 2 0.02739 astigmatism_0 2 0 0.00338 curvature 2 -2 -0.01495 astigmatism45 3 3 0.01510 trefoil_0 3 1 -0.03928 coma_x 3 -1 0.03565 coma_y 3 -3 0.01823 trefoil_30 Fitting many Zernikes for frequency 15 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 0.00093 piston 1 1 -0.01092 tilt_x 1 -1 0.01206 tilt_y 2 2 0.02699 astigmatism_0 2 0 0.00386 curvature 2 -2 -0.01577 astigmatism45 3 3 0.01466 trefoil_0 3 1 -0.03716 coma_x 3 -1 0.03859 coma_y 3 -3 0.01675 trefoil_30 Averaged 16 maps to make holo(res.mean_surface) Computing differences from mean surface (phase) Unweighted rms analysis, frequency 0 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 18.8 21.6 21.3 23.9 26 36.9 30.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.1 18.9 21.6 21.6 22.8 24.8 36.3 29.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.9 5.37 6.58 6.42 5.24 5.26 9.7 6.84 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.5 18.5 21.4 21.9 24 25.8 37 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.7 18.5 21.4 22.2 23 24.7 36.5 29.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.87 5.31 6.5 6.33 5.15 5.16 9.56 6.74 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.2 18.3 20.8 22.5 24.1 25.8 37.4 30.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.5 18.4 20.8 22.9 23 24.7 36.8 30.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.8 5.19 6.35 6.18 5.02 5.01 9.3 6.57 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.2 18.5 20.4 23.5 24.2 25.7 38 31 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.5 18.5 20.3 23.9 23 24.6 37.3 30.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.88 5.33 6.52 6.33 5.1 5 9.41 6.67 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.8 18.7 20.9 24.6 24.2 26 38.7 31.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.3 18.7 20.8 25.1 23 24.9 37.9 30.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.87 5.32 6.51 6.32 5.11 5.01 9.4 6.67 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29 18.9 21.7 25.7 24.2 26.3 39.6 31.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.5 18.8 21.6 26.2 23 25 38.8 30.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.92 5.4 6.62 6.45 5.27 5.24 9.68 6.85 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.9 18.8 22.4 26.4 24.3 26.6 39.9 31.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.4 18.8 22.4 26.8 23.1 25.2 39.2 30.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.89 5.36 6.58 6.44 5.35 5.47 9.88 6.95 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32.4 18.9 22.6 26.3 24 26.4 39.9 31.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32.8 19 22.7 26.6 22.9 24.9 39.1 30.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.87 5.32 6.55 6.43 5.41 5.62 10 7.01 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.4 18.9 22.5 25.4 23.8 26.2 39.5 30.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.7 19.1 22.7 25.4 22.7 24.7 38.8 30 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.81 5.21 6.41 6.32 5.42 5.8 10.1 7.04 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32.8 18.5 21.7 25.2 23.6 25.8 39.1 30.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.1 18.7 21.9 25.1 22.5 24.4 38.4 29.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.85 5.28 6.49 6.38 5.44 5.78 10.2 7.07 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.9 18.3 20.7 24.2 23.5 25.9 38.3 29.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.1 18.5 20.7 24.1 22.4 24.5 37.5 29.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.88 5.34 6.57 6.46 5.49 5.81 10.2 7.13 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.7 18.9 21.2 23.1 23.5 26 37.6 29.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29 19 21.2 23.2 22.4 24.6 36.8 28.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.94 5.44 6.68 6.55 5.48 5.66 10.2 7.11 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.2 19.2 21.4 22.2 23.6 26 36.9 29.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.5 19.2 21.4 22.4 22.5 24.7 36 29 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.95 5.46 6.7 6.57 5.46 5.57 10.1 7.07 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.5 19 21.4 21.5 23.5 25.8 36.4 29.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.8 19 21.5 21.7 22.5 24.5 35.6 29.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.97 5.5 6.75 6.61 5.44 5.44 9.95 7.03 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.2 18.6 21.1 21.4 23.6 25.6 36.6 30.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.6 18.5 21.2 21.6 22.6 24.3 35.7 29.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.04 5.64 6.92 6.77 5.52 5.45 10.1 7.14 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 18.1 20.6 22 23.5 25.4 37 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.3 18 20.8 22.1 22.6 24 36 29.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.07 5.69 6.99 6.82 5.54 5.37 10 7.14 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 25.7 17 18.9 20 22 24.2 36.4 28.7 Mean deviation is 2.3181623890032199 microns Taper = 10 dB, Ruze illumination-weighted rms = 27.3 micron Estimating beam: f = 650GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 650 GHz Ruze rms = 24.2 micron Centre pixel: 64.0 64.0 Value = 2758.78 (estimate), 3426.12 (perfect) Strehl = 0.648379 Strehl ratio estimate = 0.6484 Estimating beam: f = 900GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 900 GHz Ruze rms = 23.6 micron Centre pixel: 64.0 64.0 Value = 2303.92 (estimate), 3426.12 (perfect) Strehl = 0.452201 Strehl ratio estimate = 0.4522 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.15028 metres panel scale = 3.00000 metres mean frequency = 80.35300 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 -9.7 1.0 0.9 9.8 2 1 2 0.7 -2.8 15.9 16.1 3 1 3 23.4 21.0 -12.3 33.8 4 1 4 28.6 -3.9 -4.0 29.1 5 1 5 11.3 23.7 59.2 64.8 6 1 6 22.5 13.3 19.4 32.5 7 1 7 16.8 22.6 33.3 43.6 8 1 8 13.1 31.2 48.0 58.7 9 1 9 -70.3 12.6 6.8 71.8 10 1 10 -1.6 6.7 37.7 38.3 11 1 11 30.6 16.0 2.2 34.6 12 1 12 -0.7 -5.0 5.1 7.2 13 2 1 20.1 -12.4 -11.5 26.2 14 2 2 3.5 15.6 4.4 16.5 15 2 3 25.6 -8.0 -21.7 34.5 16 2 4 33.2 -14.5 2.6 36.3 17 2 5 23.1 15.0 8.5 28.8 18 2 6 10.9 20.5 37.5 44.1 19 2 7 1.8 21.5 13.1 25.2 20 2 8 27.8 13.9 4.4 31.3 21 2 9 25.4 2.0 8.4 26.8 22 2 10 27.3 7.9 13.9 31.7 23 2 11 17.1 5.1 -1.0 17.8 24 2 12 14.5 -6.7 -12.5 20.3 25 2 13 20.6 -4.6 -12.9 24.8 26 2 14 18.7 -20.7 -0.4 27.9 27 2 15 32.6 -6.4 -13.6 35.9 28 2 16 40.1 -2.4 2.5 40.3 29 2 17 10.0 9.5 -5.7 14.9 30 2 18 9.9 -3.2 -7.5 12.9 31 2 19 -3.1 -12.4 -1.2 12.9 32 2 20 23.5 -24.1 -19.2 38.7 33 2 21 11.1 -12.9 -17.8 24.6 34 2 22 16.6 -27.1 -16.9 36.1 35 2 23 19.2 -8.1 9.5 22.9 36 2 24 8.7 -3.9 -6.4 11.5 37 3 1 7.4 21.6 1.2 22.8 38 3 2 19.6 15.8 -2.3 25.2 39 3 3 -1.7 8.6 -3.1 9.3 40 3 4 9.0 10.9 20.5 24.9 41 3 5 -9.9 28.2 16.4 34.1 42 3 6 -17.3 4.7 12.9 22.1 43 3 7 -12.7 3.1 -9.4 16.0 44 3 8 -1.4 12.3 -0.9 12.5 45 3 9 19.6 7.7 -12.2 24.3 46 3 10 -2.0 7.1 -8.0 10.8 47 3 11 32.1 10.5 7.3 34.6 48 3 12 24.3 27.6 2.8 36.8 49 3 13 -5.8 18.9 9.4 21.9 50 3 14 13.5 8.2 14.1 21.2 51 3 15 2.5 8.1 21.9 23.5 52 3 16 23.6 13.8 20.5 34.2 53 3 17 25.8 18.6 8.2 32.9 54 3 18 23.0 8.0 15.8 29.0 55 3 19 21.0 5.1 -12.0 24.8 56 3 20 4.9 10.7 -1.9 11.9 57 3 21 14.5 -1.0 1.3 14.6 58 3 22 0.4 -5.3 -0.9 5.4 59 3 23 -5.1 -6.5 -3.5 9.0 60 3 24 -14.6 -5.0 -17.1 23.0 61 3 25 -8.2 -9.6 -10.5 16.4 62 3 26 -22.2 -3.0 0.6 22.5 63 3 27 -11.0 -3.2 -5.4 12.7 64 3 28 27.5 12.3 -15.1 33.7 65 3 29 18.7 9.4 -0.2 20.9 66 3 30 4.6 -8.1 -9.9 13.6 67 3 31 2.5 8.0 12.9 15.4 68 3 32 17.3 22.3 -0.9 28.2 69 3 33 23.1 23.8 32.0 46.0 70 3 34 11.5 -8.6 31.1 34.2 71 3 35 14.3 -2.7 -36.5 39.3 72 3 36 8.1 11.1 -27.8 31.1 73 3 37 3.9 11.5 -43.7 45.4 74 3 38 -3.5 -8.7 -34.1 35.4 75 3 39 -2.6 0.4 -26.1 26.2 76 3 40 19.7 -2.9 -21.8 29.5 77 3 41 6.5 -2.8 17.6 18.9 78 3 42 -1.2 13.1 0.5 13.2 79 3 43 -3.2 13.6 11.3 18.0 80 3 44 28.4 27.2 14.0 41.8 81 3 45 36.0 18.2 7.8 41.1 82 3 46 18.4 13.7 -1.1 23.0 83 3 47 29.1 16.3 -12.7 35.7 84 3 48 6.1 19.8 -19.4 28.4 85 4 1 17.4 -7.4 7.8 20.5 86 4 2 -14.9 -8.3 -5.5 17.9 87 4 3 -4.3 -13.2 -33.2 36.0 88 4 4 5.7 -3.1 -35.8 36.4 89 4 5 17.6 0.8 -27.2 32.5 90 4 6 25.4 3.3 -29.0 38.7 91 4 7 21.1 3.8 -7.5 22.7 92 4 8 4.7 5.8 -15.4 17.1 93 4 9 5.0 -1.6 -13.9 14.8 94 4 10 -9.3 -9.9 -37.2 39.6 95 4 11 -5.7 7.5 -0.0 9.4 96 4 12 -0.5 5.4 -24.8 25.4 97 4 13 -3.4 -8.0 26.9 28.3 98 4 14 -4.6 15.8 3.7 16.9 99 4 15 4.4 4.4 -1.4 6.4 100 4 16 -9.7 6.6 -1.3 11.8 101 4 17 3.4 7.9 -9.5 12.8 102 4 18 19.4 -10.6 9.1 24.0 103 4 19 1.7 -12.5 -16.7 21.0 104 4 20 1.2 -7.9 -27.2 28.3 105 4 21 -0.5 -18.1 -24.1 30.2 106 4 22 -28.3 -11.7 -13.1 33.3 107 4 23 -13.0 -37.7 -39.3 56.0 108 4 24 51.0 -7.0 -16.4 54.0 109 4 25 41.8 -6.1 11.5 43.8 110 4 26 -0.4 -10.8 -3.8 11.5 111 4 27 -16.7 -9.6 -6.5 20.3 112 4 28 -6.4 -12.4 -2.9 14.2 113 4 29 -27.9 5.5 -45.3 53.5 114 4 30 -19.8 -11.4 10.0 24.9 115 4 31 -12.4 -9.9 10.7 19.2 116 4 32 -14.7 7.9 -1.1 16.7 117 4 33 2.0 2.3 13.7 14.1 118 4 34 24.7 4.0 11.6 27.6 119 4 35 -67.5 7.8 -48.7 83.6 120 4 36 -38.0 -16.7 -44.3 60.7 121 4 37 18.6 -4.7 -31.9 37.2 122 4 38 -25.0 -31.8 -20.5 45.4 123 4 39 -15.9 -9.0 -23.7 29.9 124 4 40 -21.4 -0.4 -18.2 28.1 125 4 41 4.9 17.4 10.9 21.1 126 4 42 35.4 0.7 -6.8 36.0 127 4 43 20.0 -0.8 -21.5 29.3 128 4 44 2.2 10.5 -10.7 15.1 129 4 45 -3.1 2.4 -8.2 9.1 130 4 46 0.0 -9.5 -17.4 19.8 131 4 47 -30.6 -7.4 -52.3 61.1 132 4 48 -5.0 -8.8 -19.8 22.2 133 5 1 -11.7 9.2 7.0 16.4 134 5 2 15.6 28.6 -17.4 36.9 135 5 3 -44.6 17.4 -34.5 59.0 136 5 4 -0.5 0.0 2.9 3.0 137 5 5 -15.5 3.5 -9.6 18.6 138 5 6 -5.1 -1.1 -22.2 22.8 139 5 7 -5.6 3.8 -10.6 12.6 140 5 8 -4.3 9.0 -26.8 28.6 141 5 9 -4.3 -2.5 -4.8 6.9 142 5 10 -17.1 -3.0 -5.8 18.3 143 5 11 15.1 -14.1 -6.1 21.5 144 5 12 -23.1 4.4 0.3 23.6 145 5 13 -14.4 12.3 4.7 19.5 146 5 14 11.6 35.3 -15.1 40.1 147 5 15 -0.5 15.3 -2.1 15.5 148 5 16 -2.7 7.5 -9.0 12.0 149 5 17 -17.4 4.8 -3.3 18.4 150 5 18 3.0 -22.3 172.6 174.1 151 5 19 -20.0 -24.6 -38.2 49.6 152 5 20 -33.4 -20.4 -37.8 54.4 153 5 21 -32.1 -20.4 -29.5 48.1 154 5 22 -35.7 -13.3 -47.3 60.8 155 5 23 -37.9 -16.1 -49.2 64.2 156 5 24 -32.2 -35.2 -41.9 63.5 157 5 25 -28.4 -34.7 -37.8 58.6 158 5 26 -27.5 0.5 -40.9 49.3 159 5 27 -3.5 -2.2 -20.3 20.7 160 5 28 -2.2 -15.1 -20.2 25.3 161 5 29 12.0 -9.8 -25.3 29.7 162 5 30 6.0 -5.9 -5.5 10.0 163 5 31 5.5 -3.7 3.5 7.5 164 5 32 -3.0 6.1 14.3 15.8 165 5 33 -6.9 -5.0 0.3 8.5 166 5 34 -4.4 16.1 -6.1 17.8 167 5 35 -19.0 20.9 -60.5 66.8 168 5 36 -18.7 -25.4 -31.5 44.6 169 5 37 -8.0 -27.2 -34.6 44.7 170 5 38 -15.4 -25.2 -55.9 63.2 171 5 39 -20.3 22.1 -62.8 69.6 172 5 40 -10.7 6.7 -24.4 27.4 173 5 41 10.2 16.1 -24.7 31.2 174 5 42 -12.1 -9.3 -29.6 33.3 175 5 43 9.1 -5.3 -30.4 32.1 176 5 44 9.0 3.7 -31.6 33.1 177 5 45 5.6 6.5 -24.4 25.8 178 5 46 -9.5 -7.0 3.6 12.3 179 5 47 34.8 16.3 -38.9 54.7 180 5 48 -5.3 8.3 -11.7 15.3 181 6 1 4.2 -22.6 -41.7 47.6 182 6 2 9.4 -15.8 -54.6 57.6 183 6 3 43.2 -11.1 -18.0 48.1 184 6 4 -2.7 3.6 -14.8 15.5 185 6 5 -3.5 6.5 -7.7 10.7 186 6 6 -0.3 -2.3 -18.0 18.1 187 6 7 -13.4 -6.7 -21.6 26.3 188 6 8 -35.0 -15.0 -28.2 47.3 189 6 9 -1.6 -9.2 31.6 33.0 190 6 10 22.4 -5.1 12.5 26.2 191 6 11 -10.0 -0.3 -19.7 22.1 192 6 12 -19.0 16.2 -21.3 32.8 193 6 13 1.8 17.2 4.4 17.9 194 6 14 -10.8 6.7 -1.7 12.9 195 6 15 9.7 -5.0 18.9 21.9 196 6 16 17.2 -2.1 25.4 30.8 197 6 17 -37.6 -7.5 -17.3 42.1 198 6 18 -32.8 -22.3 -19.8 44.3 199 6 19 -35.3 -32.6 3.5 48.2 200 6 20 -17.2 -13.4 -4.9 22.4 201 6 21 -75.2 -31.3 -95.6 125.6 202 6 22 -29.4 -40.8 14.4 52.3 203 6 23 -59.9 -30.7 30.5 73.9 204 6 24 -77.2 -15.8 17.9 80.8 205 6 25 -79.5 -15.6 5.5 81.2 206 6 26 -63.2 -13.2 14.7 66.2 207 6 27 -41.8 -13.9 31.2 54.0 208 6 28 8.2 -2.4 89.3 89.7 209 6 29 -45.4 -0.3 -11.5 46.8 210 6 30 -23.0 -8.5 62.5 67.1 211 6 31 5.5 -8.8 8.5 13.4 212 6 32 -8.4 -2.5 16.5 18.6 213 6 33 28.7 8.4 142.5 145.6 214 6 34 31.8 12.0 46.1 57.3 215 6 35 -40.3 23.5 32.0 56.6 216 6 36 -19.7 16.1 61.5 66.6 217 6 37 -40.2 -2.7 35.6 53.7 218 6 38 -38.2 -9.9 -13.4 41.7 219 6 39 1.6 6.1 20.8 21.8 220 6 40 -21.5 11.6 19.2 31.0 221 6 41 -26.4 9.0 -13.1 30.8 222 6 42 -10.8 -18.0 10.7 23.6 223 6 43 -12.6 -18.4 4.3 22.8 224 6 44 -25.0 12.2 -15.2 31.7 225 6 45 -18.9 -1.3 -5.6 19.8 226 6 46 17.7 -17.4 6.5 25.7 227 6 47 -13.6 -24.3 -45.3 53.2 228 6 48 -26.0 -23.4 -46.5 58.2 229 7 1 -32.6 22.3 -14.6 42.1 230 7 2 -31.6 -5.4 -32.2 45.5 231 7 3 0.3 1.2 -5.4 5.5 232 7 4 4.4 73.7 33.8 81.2 233 7 5 -19.9 6.0 34.6 40.4 234 7 6 2.7 38.8 6.3 39.4 235 7 7 -21.2 31.0 34.1 50.7 236 7 8 10.1 44.3 -42.7 62.4 237 7 9 29.4 19.6 52.4 63.2 238 7 10 15.3 20.4 15.8 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-1 8 33 1 8 34 3 8 35 -3 8 36 -3 8 37 -1 8 38 -1 8 39 1 8 40 3 8 41 -3 8 42 -6 8 43 -7 8 44 -2 8 45 3 8 46 -13 8 47 1 8 48 -8 8 49 3 8 50 2 8 51 0 8 52 0 8 53 0 8 54 12 8 55 -3 8 56 -2 8 57 1 8 58 9 8 59 4 8 60 14 8 61 0 8 62 2 8 63 5 8 64 2 8 65 10 8 66 -4 8 67 0 8 68 6 8 69 5 9 1 18 9 2 14 9 3 14 9 4 18 9 5 4 9 6 -6 9 7 7 9 8 27 9 9 8 9 10 9 9 11 7 9 12 -12 9 13 16 9 14 20 9 15 14 9 16 14 9 17 3 9 18 9 9 19 34 9 20 -47 9 21 21 9 22 43 9 23 2 9 24 8 9 25 -9 9 26 -7 9 27 -5 9 28 -13 9 29 -5 9 30 -11 9 31 -18 9 32 6 9 33 -5 9 34 -14 9 35 2 9 36 -20 9 37 -1 9 38 4 9 39 -1 9 40 3 9 41 1 9 42 7 9 43 0 9 44 -1 9 45 -2 9 46 4 9 47 0 9 48 0 9 49 -11 9 50 0 9 51 4 9 52 -2 9 53 0 9 54 3 9 55 9 9 56 -2 9 57 3 9 58 3 9 59 -21 9 60 2 9 61 9 9 62 7 9 63 7 9 64 -3 9 65 3 9 66 -1 9 67 -8 9 68 3 9 69 2 10 1 6 10 2 35 10 3 17 10 4 5 10 5 3 10 6 -6 10 7 9 10 8 21 10 9 11 10 10 6 10 11 1 10 12 0 10 13 -3 10 14 15 10 15 1 10 16 -4 10 17 -3 10 18 -11 10 19 9 10 20 15 10 21 3 10 22 10 10 23 0 10 24 -12 10 25 -7 10 26 2 10 27 -3 10 28 -5 10 29 0 10 30 -6 10 31 -19 10 32 6 10 33 -6 10 34 -7 10 35 -2 10 36 -4 10 37 -17 10 38 -7 10 39 -4 10 40 -6 10 41 -9 10 42 -7 10 43 -10 10 44 -8 10 45 -2 10 46 -9 10 47 -1 10 48 5 10 49 -7 10 50 0 10 51 0 10 52 -5 10 53 -7 10 54 7 10 55 -10 10 56 -2 10 57 -1 10 58 2 10 59 0 10 60 11 10 61 -13 10 62 3 10 63 1 10 64 -3 10 65 0 10 66 0 10 67 -6 10 68 0 10 69 6 11 1 -7 11 2 1 11 3 -3 11 4 -4 11 5 3 11 6 -7 11 7 -20 11 8 2 11 9 -16 11 10 1 11 11 -5 11 12 -3 11 13 0 11 14 1 11 15 6 11 16 3 11 17 -5 11 18 -3 11 19 8 11 20 7 11 21 6 11 22 -4 11 23 2 11 24 -8 11 25 -9 11 26 1 11 27 2 11 28 -3 11 29 3 11 30 0 11 31 -9 11 32 -1 11 33 2 11 34 -6 11 35 0 11 36 6 11 37 -9 11 38 -2 11 39 -3 11 40 -2 11 41 0 11 42 10 11 43 -7 11 44 4 11 45 3 11 46 3 11 47 5 11 48 1 11 49 3 11 50 4 11 51 0 11 52 -5 11 53 -8 11 54 5 11 55 0 11 56 4 11 57 0 11 58 4 11 59 9 11 60 0 11 61 5 11 62 0 11 63 1 11 64 -2 11 65 3 11 66 -5 11 67 4 11 68 8 11 69 8 12 1 9 12 2 46 12 3 -2 12 4 -14 12 5 -7 12 6 -7 12 7 -1 12 8 11 12 9 3 12 10 -13 12 11 -7 12 12 -4 12 13 0 12 14 10 12 15 5 12 16 1 12 17 -5 12 18 5 12 19 18 12 20 -11 12 21 -1 12 22 -1 12 23 0 12 24 -5 12 25 -3 12 26 2 12 27 -1 12 28 -6 12 29 -2 12 30 -1 12 31 -11 12 32 4 12 33 10 12 34 -16 12 35 -2 12 36 -9 12 37 1 12 38 -2 12 39 -2 12 40 -5 12 41 -2 12 42 0 12 43 -7 12 44 1 12 45 1 12 46 -2 12 47 0 12 48 0 12 49 -3 12 50 4 12 51 8 12 52 -1 12 53 -1 12 54 2 12 55 0 12 56 4 12 57 5 12 58 -1 12 59 0 12 60 1 12 61 2 12 62 5 12 63 11 12 64 -3 12 65 5 12 66 2 12 67 -5 12 68 6 12 69 1 Adjuster movements: rms = 29.9 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20041115-151700 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1 Reducing ID = 20041111-194955 Data directory /net/moana/export/data/janw/rxh3 contains 138 data files Reading database file: /home/janw/rxh3/Rxh3red/rxh3db.dat Resolved file ID 20041111-194955 = rxh3-20041111-194955.fits Reducing file ID 20041111-194955 Found database entry for 20041111-194955 Setting data.pointing_offset_x = -0.64 Setting data.pointing_offset_y = 19.32 Setting data.secondary_defocus_offset = 2.79 Reducing data file rxh3-20041111-194955.fits at Mon Nov 15 15:52:46 HST 2004 Reduction code ID: 2.20 (created Apr 27 2004 at 15:09:15) (TDL_BIN = /.automount/moana/root/export/data/janw/install/tdl_2p21_test2) Comment: Deleting data and results from internal arrays Created output directory: /home/janw/rxh3/Rxh3red/20041111-194955 Created output directory: /home/janw/rxh3/Rxh3red/20041111-194955/default Deleting all files in /home/janw/rxh3/Rxh3red/20041111-194955/default ... ... 0 files deleted.